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| Content Provider | IET Digital Library |
|---|---|
| Author | Namburu, Anupama Samayamantula, Srinivas Kumar Edara, Srinivasa Reddy |
| Abstract | Intuitionistic fuzzy sets (IFSs), rough sets are efficient tools to handle uncertainty and vagueness present in images and recently are combined to segment medical images in the presence of noise and intensity non homogeneity (INU). These hybrid algorithms are sensitive to initial centroids, parameter tuning and dependency with the fuzzy membership function to define the IFS. In this paper, a novel clustering algorithm, namely generalized rough intutionistic fuzzy c-means (GRIFCM) is proposed for brain magnetic resonance (MR) image segmentation avoiding the dependency with the fuzzy membership function. In this algorithm, each pixel is categorized into three rough regions based on the thresholds obtained by the image data by minimizing the noise. These regions are used to create IFS. The distance measure based on IFS eliminate's the influence of noise and INU present in the image producing accurate brain tissue segmentation. The proposed algorithm is evaluated through simulation and compared it with existing k-means (KM), fuzzy c-means (FCM), Rough fuzzy c-means (RFCM), Generalized rough fuzzy c-means (GRFCM), soft rough fuzzy c-means (SRFCM) and rough intuitionistic fuzzy c-means (RIFCM) algorithms. Experimental results prove the superiority of the proposed algorithm over the considered algorithms in all analyzed scenarios. |
| Starting Page | 777 |
| Ending Page | 785 |
| Page Count | 9 |
| ISSN | 17519659 |
| Volume Number | 11 |
| e-ISSN | 17519667 |
| Issue Number | Issue 9, Sep (2017) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-ipr/11/9 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2016.0891 |
| Journal | IET Image Processing |
| Publisher Date | 2017-06-27 |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Algebra Biological Tissues Biology And Medical Computing Biomedical Magnetic Resonance Imaging Biomedical MRI Biophysics of Neurophysiological Processes Brain Brain Tissue Segmentation Cluster Standardisation Clustering Algorithm Combinatorial Mathematics Computer Vision And Image Processing Technique FCM Fuzzy Membership Function Dependency Fuzzy Set Theory Generalised Rough Intuitionistic Fuzzy C-means Graph Theory Hybrid Algorithm IFS Image Denoising Image Segmentation Initial Centroids Intensity Non-homogeneity Intuitionistic Fuzzy Set Magnetic Resonance Brain Image Segmentation Medical Image Processing Medical Image Segmentation Medical Magnetic Resonance Imaging And Spectroscopy Neurophysiology Noise Influence Elimination Noise Minimisation Optical, Image And Video Signal Processing Parameter Tuning Patient Diagnostic Method And Instrumentation Pattern Clustering Rough Set Rough Set Theory Set Theory Spectroscopy Uncertainty Handling |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
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